1 Short and Long-Run Effects of Macroeconomic Variables on The
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Short and Long-run Effects of Macroeconomic Variables on the Spanish Agricultural Sector Monia Ben KAABIA and José M. GIL Unidad de Economia Agraria - SIA – DGA Apdo. 727; 50080 Zaragoza (Spain) ABSTRACT In this paper, the effect of some relevant macroeconomic variables on Spanish agricultural prices and exports is analysed. The methodological approach used is based on the cointegration procedure making the distinction between short- and long-run effects possible. A eight variables system in real terms is specified. Long-run analysis indicates that money income neutrality as well as agricultural prices homogeneity hold. Short-run dynamics has been analysed by specifying a Structural Vector Error Correction Model. Main results indicate that, in general terms, agricultural variables do not significantly affect macroeconomic variables. In the very short run farmers will benefit from increases of money and general prices while over longer horizons the agricultural terms of trade get worse. Key words: macroeconomics, agriculture, cointegration; Spain, short and long-run. 1 1. INTRODUCTION Changes in the macroeconomic policy have become increasingly significant within the agrofood sector as agriculture has become more capitalized and more dependent on international markets, then being more vulnerable to variations in interest rates, exchange rates and international growth rates. As a consequence, since the mid seventies, a number of theoretical and empirical studies have analysed the impact of macroeconomic variables on the relative performance of the agricultural sector. In the early studies, macroeconomic variables (income, interest rate, exports,...) were introduced as purely exogenous in agricultural sector models. It was considered that the agricultural sector was a closed system, being only influenced by a few general economic variables (In and Mount, 1994). The paper by Schuh (1974) could be considered as the starting point of a second group of studies emphasizing the role of exchange rate in explaining agricultural variable fluctuations. In a partial equilibrium framework and considering the exchange rate as an exogenous variable, Chambers and Just (1979, 1981), Longmire and Morey (1983), and Batten and Belongia (1986) provide empirical evidence of such an effect while other studies conclude that exchange rate movements have little effect on the variability of real commodity prices (Collins et al. 1980). However, these empirical investigations neglect not only the possible effect of exchange rate changes on other macroeconomic variables (which can influence agricultural prices and exports indirectly) but also the effects of other macroeconomic variables (such as interest rates) both on exchange rate and agricultural variables. In this context, Chambers (1984) develops a general equilibrium model in order to analyse the effect of macroeconomic variables on agricultural trade where the exchange rate, income, interest rate as well as usual agricultural variables are treated as endogenous. This author concludes that tight monetary policy hurts the agricultural sector as a result of exchange rate appreciation and rising interest rates. Finally, it is possible to identify a third group of papers dealing with the analysis of the dynamic linkages between monetary variables and the agricultural sector. Among this group of studies, considerable attention has been paid to the reaction of agricultural and non- agricultural prices to monetary shocks. The question of money neutrality in the agricultural sector, and the speed of price adjustments, has been considered of central importance for policy analysis (Bordo, 1980; Tweeten, 1980, Bessler and Babula, 1987; Devadoss and 2 Meyers, 1987; Taylor and Spriggs, 1989; Robertson and Orden, 1990; Larue and Babula, 1994; Dorfman and Lastrapes, 1996, among others). Results from most of the above mentioned studies, although mainly related to the United States and Canada1, substantially differ from each other and, in many cases, they are even contradictory. There exist alternative explanations for such differences: samples are not homogeneous, the number of variables included differs as well as their treatment as endogenous or exogenous, and the different methodological approaches used. However, there seems to exist a consensus on the fact that models analysing macroeconomic linkages to the agricultural sector should include the more relevant macroeconomic variables of the country being analysed and should treat them as endogenous (Devadoss et al., 1987; Taylor and Spriggs, 1989; Denbaly and Torgerson, 1991; Thraen et al., 1992; In and Mount, 1994; among others). Partly for this reason, most of the analyses on this topic have recently been conducted using Vector Autoregression (VAR) models. In VAR models all variables are considered endogenous. Moreover, it is possible to calculate the short-run responses of a shock in one variable in the system on any other variable offering a convenient way to characterize data without having to involve economic theory to restrict the dynamic relationships among variables. Cooley and LeRoy (1985), among others, have criticized the usefulness of such an atheoretical approach for policy analysis. To overcome this problem "Structural" VAR (SVAR) models have been used (Bernanke, 1986, Sims, 1986 and Blanchard and Quah, 1989) which allow the researcher to specify and test restrictions based on economic theory prior to calculating the impulse response functions (Orden and Fackler, 1989). Finally, recent developments on time series analysis have modified the econometric framework to analyse the relationships between macroeconomic variables and the agricultural sector. The concepts of non-stationarity and cointegration have become very popular and have to be explicitly tested to properly specify an econometric model. In this new context, Johansen (1988) and Johansen and Juselius (1990, 1992 and 1994) provide an interesting methodology that allows the researcher to distinguish between the short and the long run. On the one hand, it is possible to identify the long-run structural relationships among a set of variables and how variables in the system adjusts to deviations from such long-run equilibrium relationships. On the other, it is possible to calculate the impulse response 3 functions in a similar way to that in the SVAR models. This distinction is useful as economic restrictions are considered long run in nature while it is also interesting, for policy analysis, to know how the system adjust to disequilibrium. The objective of this paper is to use recent developments in time series analysis to explain the relationships between macroeconomic variables and the agricultural sector in Spain. Special attention is paid to the distinction between long-run structural relationships and short-run dynamics. The paper is one of the first attempts to analyse such relationships in Spain. The paper is organized as follows. The data used in this study are described in section 2 as well as results from non-stationary tests. Long-run equilibrium relationships are analysed in section 3. The short-run dynamics is considered in section 4. Finally, some concluding remarks are outlined. 2. DATA AND METHODOLOGICAL APPROACH In order to carry out the empirical analysis of the linkages between macroeconomic variables and the agricultural sector, two blocks of variables have been considered. The first one is the macroeconomic block which contains the more relevant macroeconomic variables: 1) real effective exchange rate (ER) (the real multilateral exchange rate2 taking into account world and Spanish consumer price indices); 2) the real money supply (RM) (money supply3 divided by the consumer price index); 3) interest rate (R) (the three-month money market interest rate); 4) inflation expressed as consumer price index in first differences (P); and 5) real gross domestic product (Y). The second one is the agricultural block, which includes the following variables: 1) real farm input prices (RIP); 2) real farm output prices (ROP) (real farm input prices and real farm output prices are calculated as nominal prices divided by the consumer price index) and 3) real agricultural exports (AX)4 (exports value divided by the agricultural exports price index). These variables were chosen because it was felt that they would capture the most important relationships between both sectors. Besides, as the sample period is limited, it has been attempted to use as few variables as possible. Quarterly data from 1978:1 to 1995:4 are used. All variables are in logarithms, except for the interest rate which is in a percentage form 4 and is divided by one hundred to make the estimated coefficients comparable with logarithmic changes. Finally, all variables have been deseasonalised5. Time series univariate properties have been examined by using unit root tests. As in small samples such tests have limited power (Blough, 1992), two alternative tests developed by Dickey and Fuller (1979, 1981) (DFA) and Kwiatkowski et al.(1992) (KPSS) have been applied. Both tests indicated that all variables were I(1)6 Thus, the methodological approach used in this paper consists of three steps: first, the Johansen’s (1988) multivariate contegration procedure is used to test if variables are cointegrated; second, cointegration vectors are identified as long-run meaningful economic relationships; finally, impulse response functions are computed to analyse short-run dynamics 3. LONG-RUN ANALYSIS The starting point of Johansen’s